PHPCLANCHILDES with regular expressions

9 matches in 9 utterances

3.23 per 1,000 words of everyone but CHI, in 1 of 1 transcripts (649 utterances, 2,790 words searched).

  1. they made these up. MOT · downs-flusberg/jerryt.cha, line 205
  2. do you see these socks? MOT · downs-flusberg/jerryt.cha, line 246
  3. look at these feet. MOT · downs-flusberg/jerryt.cha, line 494
  4. ok, we don't need all of these. MOT · downs-flusberg/jerryt.cha, line 721
  5. you know what's wrong with these? MOT · downs-flusberg/jerryt.cha, line 759
  6. these are really mixed up. MOT · downs-flusberg/jerryt.cha, line 770
  7. how many of these are we gonna have each? MOT · downs-flusberg/jerryt.cha, line 777
  8. let's deal these. MOT · downs-flusberg/jerryt.cha, line 790
  9. do you have one of these? MOT · downs-flusberg/jerryt.cha, line 908
  1. MOTyeah.
    CHIlumpty.
    MOT*MOT: they made these up.
    CHIand gumpty.
    MOTand gumpty.
  2. MOTyeah.
    MOTyou know they have socks on?
    MOT*MOT: do you see these socks?
    MOTyou want to give him socks?
    MOTboy, he certainly is going to be yellow.
  3. MOTwrong body on the wrong head.
    CHIwrong head [$0a].
    MOT*MOT: look at these feet.
    MOTwhat do you think they belong to?
    CHIbelong to sam.
  4. CHInot susan, that's curly.
    MOT<oh> [/?].
    MOT*MOT: ok, we don't need all of these.
    CHIwhy?
    MOTwell, it's too many.
  5. CHIback on there.
    MOTyeah.
    MOT*MOT: you know what's wrong with these?
    MOTsome of them aren't going the right way.
    CHIright way [$0a].
  6. CHII be dealer [$0a] [$0will].
    MOTwait a second.
    MOT*MOT: these are really mixed up.
    CHImixed up.
    CHIwhat?
  7. CHIare you serious?
    MOTI'm serious.
    MOT*MOT: how many of these are we gonna have each?
    MOTfive?
    MOTplease don't shoot that.
  8. MOTshoot it at the couch.
    MOT<whoops> [/?].
    MOT*MOT: let's deal these.
    CHImissed.
    MOTyou did it.
  9. MOTinteresting.
    MOTalright.
    MOT*MOT: do you have one of these?
    CHIno.
    MOTwhat do I do?

Matches by child

Matches per 1,000 words, all transcripts of each child together, highest first.

  1. Jerryt downs-flusberg3.23
All transcripts as a table
TranscriptChildAgeWordsUtterances matchedMatchesPer 1,000 words
downs-flusberg/jerryt.chaJerryt 2,790993.23

What the pattern matched

1 different forms (lowercased). Useful to see what a pattern really catches: unexpected forms here usually mean the pattern is too broad.

  1. these9 · 100.0%